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Background <p>Inter-tumor heterogeneity poses significant challenges for precision therapy in thyroid cancer (TC). The conventional organoid models are limited by inefficiency and poor physiological relevance.</p> Methods <p>We developed droplet-engineered organoids (DEOs) using microfluidic 3D bioprinting to rapidly generate patient-derived TC models. These DEOs were characterized via histology, whole-exome and RNA sequencing, and utilized for drug sensitivity testing and metastasis modeling.</p> Results <p>DEOs were generated within 10 days, exhibiting superior uniformity (CV: 2.54%) and a high success rate (76%). They faithfully recapitulated the histopathological architecture, genomic landscape (92% driver gene concordance), and native immune microenvironment (CD3+/CD56+/CD68+/α-SMA+) of parental tumors. Drug screening revealed patient-specific heterogeneity, accurately mirroring clinical responses, including cisplatin sensitivity and anti-PD-1 resistance. We established a novel TC and lung organoids co-culture model, which could be used to study the TC lung metastasis. Crucially, transcriptomics identified stage-specific maturation driven by NF-κB signaling. Pharmacological inhibition of NF-κB synergistically enhanced the efficacy of dasatinib, anti-PD-1, and paclitaxel, with combination index (CI) values of 0.58, 0.45, and 0.80, respectively.</p> Conclusions <p>Our microfluidic platform enables rapid, high-fidelity modeling of TC, offering a scalable and physiologically relevant tool for mechanistic studies, drug screening, and personalized therapy prediction, with highly promising translational potential.</p>

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Microfluidic-based patient-derived organoids recapitulate thyroid cancer heterogeneity and reveal NF-κB-driven maturation for precision therapy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月27日

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  • Hengyuan Gao,
  • Junqing Lin,
  • Xiaobing Chen,
  • Yingshi Su,
  • Yibin Huang,
  • Yubo Zhang,
  • Junchang Zhang,
  • Nan Xu,
  • Xiaoyong Dai

摘要

Background

Inter-tumor heterogeneity poses significant challenges for precision therapy in thyroid cancer (TC). The conventional organoid models are limited by inefficiency and poor physiological relevance.

Methods

We developed droplet-engineered organoids (DEOs) using microfluidic 3D bioprinting to rapidly generate patient-derived TC models. These DEOs were characterized via histology, whole-exome and RNA sequencing, and utilized for drug sensitivity testing and metastasis modeling.

Results

DEOs were generated within 10 days, exhibiting superior uniformity (CV: 2.54%) and a high success rate (76%). They faithfully recapitulated the histopathological architecture, genomic landscape (92% driver gene concordance), and native immune microenvironment (CD3+/CD56+/CD68+/α-SMA+) of parental tumors. Drug screening revealed patient-specific heterogeneity, accurately mirroring clinical responses, including cisplatin sensitivity and anti-PD-1 resistance. We established a novel TC and lung organoids co-culture model, which could be used to study the TC lung metastasis. Crucially, transcriptomics identified stage-specific maturation driven by NF-κB signaling. Pharmacological inhibition of NF-κB synergistically enhanced the efficacy of dasatinib, anti-PD-1, and paclitaxel, with combination index (CI) values of 0.58, 0.45, and 0.80, respectively.

Conclusions

Our microfluidic platform enables rapid, high-fidelity modeling of TC, offering a scalable and physiologically relevant tool for mechanistic studies, drug screening, and personalized therapy prediction, with highly promising translational potential.